TDTR

src/globalization/trs_solvers/solvers/TDTR.jl

@@ -0,0 +1,32 @@
+
+a = ∇f[1]
+c = ∇f[2]
+b = Λ[1]
+d = Λ[2]
+e = Δ^2
+
+k1 = a+c-b^2*e-d^2*e
+k2 = d*e
+K = k1 -4*b*k2
+J = k1 +2*b*k2
+L = -b*c-a*d +b^2*k2+b*d^2*e
+H = b^2*c+a*d^2-b^2*d^2*e
+B = b*e+k2
+C = 108*B^2*H+72*e*H*K+2*K^3-36*B*K*L-108*e*L^2+sqrt(-4*(-12*e*H+K^2-12*B*L)^3+(108*B^2*H+72*e*H*K+2*K^3-36*B*K*L-108*e*L^2)^2)
+g = b+d
+
+U = -((2^(2/3)*C^(1/3) - 6*e*g^2 + (2*2^(1/3)*J^2)/C^(1/3) - 4*K)/e)
+W =  ((2^(2/3)*C^(1/3) - 6*e*g^2 + (2*2^(1/3)*J^2)/C^(1/3) - 4*K)/e)
+V = C^(1/3)/(3*2^(1/3)*e) + 2*g^2 + (2^(1/3)*J^2)/(3*C^(1/3)*e) + (4*K)/(3*e)
+Y = 2 *sqrt(6)*(e*g^3 + g*K + 2*L)
+Q = V - Y/(e Sqrt[U])
+R = V + Y/(e Sqrt[U])
+
+
+sol1 = 1/12 * (-6g-6sqrt(R)-sqrt(6)*sqrt(U))
+sol2 = 1/12 * (-6g+6sqrt(R)-sqrt(6)*sqrt(U))
+sol3 = 1/12 * (-6g-6sqrt(R)+sqrt(6)*sqrt(U))
+sol4 = 1/12 * (-6g+6sqrt(R)+sqrt(6)*sqrt(U))
+
+
+

src/optimize/problem_types.jl

@@ -215,15 +215,15 @@ struct OptimizationOptions{T1,T2,T3,T4,Txn,Tgn}
 end
 
 OptimizationOptions(;
-    x_abstol = 0.0,
-    x_reltol = 0.0,
+    x_abstol = 0,
+    x_reltol = 0,
     x_norm = x -> norm(x, Inf),
     g_abstol = 1e-8,
     g_reltol = 0.0,
     g_norm = x -> norm(x, Inf),
     f_limit = -Inf,
-    f_abstol = 0.0,
-    f_reltol = 0.0,
+    f_abstol = -Inf, # 
+    f_reltol = -Inf, # Not useful at 0 if for example we have quadric and trust region accept but objective is the same
     nm_tol = 1e-8,
     maxiter = 10000,
     show_trace = false,

test/optimize/param.jl

@@ -0,0 +1,27 @@
+@testset "param test" begin
+    N_test = 9
+    w = rand(N_test)
+    function obji(x, data)
+        s=sum((x .- data) .^ 2)
+        s
+    end
+    function g!(G, x, data)
+        G .= 2 * (x .- data)
+        G
+    end
+    function h!(H, x, data)
+        H .=  2 * I
+        H
+    end
+    param1 = [1, 2, 3]
+    sc = ScalarObjective(; f = obji, g = g!, h = h!, param = param1)
+    op = OptimizationProblem(sc)
+    sol1 = solve(op, [3.0, 4.0, 4.0], BFGS(), OptimizationOptions())
+    @test sol1.info.solution ≈  param1
+
+    param2 = [10, 20, 30]
+    sc = ScalarObjective(; f = obji, g = g!, h = h!, param = param2)
+    op = OptimizationProblem(sc)
+    sol2 = solve(op, [3.0, 4.0, 4.0], BFGS(), OptimizationOptions())
+    @test sol2.info.solution ≈  param2
+end

test/optimize/preconditioning.jl

@@ -29,7 +29,7 @@ using Test
                     OPT_PROBS["laplacian"]["array"]["mutating"],
                     copy(initial_x),
                     optimizer(P),
-                    OptimizationOptions(g_abstol = 1e-6),
+                    OptimizationOptions(g_abstol = 1e-6, f_abstol = 0.0),
                 )
                 push!(mino, results.info.minimum)
                 push!(iter, results.info.iter)

test/runtests.jl

@@ -14,5 +14,6 @@ include("optimize/problems.jl")
 include("optimize/interface.jl")
 include("optimize/preconditioning.jl")
 include("optimize/complex.jl")
+include("optimize/param.jl")
 include("lsqfit/interface.jl")
 include("globalization/runtests.jl")